Method and apparatus for continuous pulse contour cardiac output

ABSTRACT

A system and method are provided for sensing cardiac electrogram (EGM) signals and ventricular pressure signals and for using the sensed EGM and sensed pressure signals for estimating stroke volume (SV). A measure of cardiac output can be computed from the estimated SV and a heart rate determined from the EGM signals. The sensed ventricular pressure signal and the sensed EGM signal are used to derive landmark points such as an estimated pulmonary diastolic pressure, a mean pulmonary artery pressure, a peak right ventricular pressure (RVP), and various time intervals used in computing an area or a pulse contour integral. The pulse contour integral is used to estimate SV. The estimated pulmonary diastolic pressure, mean pulmonary artery pressure and CO computed from the estimated SV can be used to compute a pulmonary vascular resistance.

CROSS REFERENCE TO PRIORITY APPLICATION

This application is a continuation of U.S. patent application Ser. No.12/124,847, filed May 21, 2008, U.S. Pat. No. 7,507,208, which is acontinuation of U.S. patent application Ser. No. 11/045,573, filed Jan.27, 2005, now abandoned, both of which are incorporated by referenceherein.

FIELD OF THE INVENTION

The present invention relates generally to hemodynamic monitoringdevices and methods and particularly to a method and apparatus formonitoring cardiac output using ventricular pressure signals.

BACKGROUND OF THE INVENTION

Implantable hemodynamic monitors are available for monitoring rightventricular pressure chronically in an ambulatory patient. Patients withcongestive heart failure (CHF) have elevated cardiac filling pressuresand reduced cardiac output. A major treatment objective is to lowerfilling pressures while maintaining adequate cardiac output. Therefore,from a hemodynamic monitoring perspective, it is advantageous to monitorboth filling pressures and measures of cardiac output.

BRIEF SUMMARY OF THE INVENTION

The present invention provides a system and method for monitoringcardiac output estimated from a ventricular pressure signal using pulsecontour analysis. In one embodiment, the right ventricular pressure(RVP) signal is acquired from an implantable pressure sensor deployed inthe right ventricle. The RVP contour is analyzed to estimate strokevolume (SV) during cardiac systole, from which an estimate of forwardflow can be derived.

The system includes a pressure sensor adapted for implantation in theright ventricular chamber for sensing the RVP signal. The system mayoptionally include an electrode for measuring cardiac electricalsignals, such as an intracardiac electrogram (EGM). The electrode andpressure sensor are coupled to an implantable cardiac monitoring deviceincluding signal recovery circuitry, processing circuitry, andassociated memory for acquiring and storing heart rate (from the EGM)and RVP signal information. The RVP signals are processed by themicroprocessor to estimate SV on a beat-by-beat basis when cardiacoutput monitoring is enabled. The implantable cardiac monitoring deviceis equipped with telemetry circuitry for communicating with an externalprogrammer. RVP data or estimated SV data in digital units along withheart rate and any other relevant data may be uplinked to the externalprogrammer and further processed by a microprocessor included in theexternal programmer or transferred to another computer for computing anactual flow value using patient-specific calibration,

In an associated method for estimating SV from the RVP signal, landmarkpoints are identified on the RVP contour during the systolic timeinterval. The start of the systolic time interval is identified bydetecting an R-wave event. An analysis window is set upon detecting anR-wave event. The analysis window duration is a predetermined intervalset to include the systolic time interval. The RVP signal is acquiredand stored in a memory buffer during the analysis window to allowidentification of landmark points and computation of the estimated SV.

In one embodiment, the landmark points identified for use in computingan estimated SV are the peak RVP and the estimated pulmonary arterydiastolic (ePAD) pressure, which is equal to the RVP signal amplitude atthe time of the maximum rate of rise in RVP (dP/dt max). A measure ofestimated SV is computed as the difference between peak RVP and ePAD.

In another embodiment, the area under the pressure pulse is approximatedusing polygonal (e.g. triangular, rectangular, or trapezoidal) shapeswhose vertices or sides are defined by various landmarks of the RVPpulse. The vertices and sides of the polygons can be defined by thevalues or times of occurrence of dP/dt max, dP/dt min, a single globalor multiple local pressure peaks during systole, ePAD, RVP at dP/dt min,RVP where the descending RVP contour equals the mean PA pressure, andinflection points between multiple local peaks that sometimes occur onthe RVP waveform. There may be other landmarks on the RVP waveform thatare useful, besides those listed above.

In yet another embodiment, a pulse contour integral is computed as anestimate of SV. Landmark points are identified on the RVP signal for useas an integration start time and an integration end time. Theintegration start time corresponds to the start of the systolic ejectioninterval which is marked by the opening of the pulmonic valve. In oneembodiment, integration start time is identified as the time of dP/dtmax or ePAD. The integration end time corresponds to the end of thesystolic ejection interval, marked by closure of the pulmonic valve. Inone embodiment, integration end time is identified as the time that thedescending RVP contour equals ePAD. An area defined by the RVP contourduring the integration time interval is computed and may be used toderive an estimate of SV.

In some embodiments, the estimated SV computed as the area under the RVPcontour during the integration time interval is corrected by a number ofcorrection areas. Correction areas are computed based on landmark pointson the RV pressure signal. Correction areas are used to compute a pulsecontour integral (PCI) that more accurately represents the pulmonaryartery flow contour and accordingly provides a more accurate estimate ofSV.

An estimated SV can be used to compute a measure of cardiac output (CO)by dividing the estimated SV by the R-R interval (RRI) on a beat-by-beatbasis. The estimated SV and CO will be in digital units. These digitalvalues may be used by the IMD in closed loop control methods formanaging device-delivered therapies. SV and CO estimates computed indigital units may be uplinked to an external device and converted toactual volume and flow units using patient-specific calibration values.

In some embodiments, additional hemodynamic monitoring parameters areestimated from the right ventricular pressure signal including meanpulmonary artery pressure (MPAP) and pulmonary vascular resistance (PVR)to provide a set of meaningful hemodynamic diagnostics for use inmanaging cardiac disease.

Practice of the present invention for estimating stroke volume andcardiac output from a ventricular pressure signal is not limited tousing the RVP signal. Use of the RVP signal allows estimation ofpulmonary artery pressures at various time points in the cardiac cyclewhich further allows estimation of flow. However, a left ventricularpressure (LVP) signal may be obtained for use in estimating aorticpressures at various time points in the cardiac cycle which may befurther used for estimating flow. Since flow from the left and rightventricles is equal over time, estimation of cardiac output from eitherleft or right ventricular pressure signals can be used. As such, variousembodiments of the present invention include approximating an estimatedstroke volume as an area under the left ventricular pressure pulse usingpolygonal shapes whose vertices or sides are defined by variouslandmarks of the LVP pulse, or computing a pulse contour integral as anestimate of SV based on an integration start time and an integration endtime derived from landmark points on the LVP signal.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is an illustration of an exemplary implantable medical device(IMD) configured to monitor a patient's heart.

FIG. 2 is a block diagram summarizing the data acquisition andprocessing functions for the IMD shown in FIG. 1.

FIG. 3 is a flow chart summarizing a method for computing an estimatedSV from a right ventricular pressure signal for use in CO monitoring.

FIG. 4 shows a RVP signal and illustrates one method for estimating SVfrom the RVP signal.

FIG. 5 illustrates a method for determining an integration interval foruse in computing a pressure pulse contour integral in an alternativemethod for estimating SV from the RVP signal.

FIG. 6 illustrates a method for computing two correction areas, A2 andA3, used in calculating a RVP pulse contour integral for estimating SV.

FIG. 7 illustrates a method for computing an estimated mean pulmonaryartery pressure from the RVP signal.

FIG. 8 illustrates the computation of a third correction area, A4, thatmay be used in computing a RVP pulse contour integral for estimating SVcomputed.

FIG. 9 illustrates the computation of a fourth correction area, A5, thatmay be used in computing a RVP pulse contour integral for estimating SV.

FIG. 10 illustrates the computation of a pulse contour integral (PCI)from the total area A1 under RVP waveform between integration start timeand integration end time and the correction areas A2, A3, A4 and A5.

FIG. 11 is a plot of estimated SV computed using the RVP pulse contourmethod provided by the invention versus stroke volume measured byplacing a flow probe on the pulmonary artery in a canine study.

FIG. 12 is a flow chart summarizing the steps performed in a method formonitoring cardiac output using the RVP pulse contour method forestimating SV as described in conjunction with FIGS. 5 through 9.

FIG. 13 is a flow chart summarizing a method for monitoring thehemodynamic status of a patient.

DETAILED DESCRIPTION

FIG. 1 is an illustration of an exemplary implantable medical device(IMD) 100 connected to monitor a patient's heart 120. IMD 100 may beconfigured to integrate both monitoring and therapy features, as will bedescribed below. IMD 100 collects and processes data about heart 120from one or more sensors including a pressure sensor and an electrodefor sensing cardiac electrogram (EGM) signals. IMD 100 may furtherprovide therapy or other response to the patient as appropriate, and asdescribed more fully below. As shown in FIG. 1 IMD 100 may be generallyflat and thin to permit subcutaneous implantation within a human body,e.g., within upper thoracic regions or the lower abdominal region. IMD100 is provided with a hermetically-sealed housing that encloses aprocessor 102, a digital memory 104, and other components as appropriateto produce the desired functionalities of the device. In variousembodiments, IMD 100 is implemented as any implanted medical devicecapable of measuring the heart rate of a patient and a ventricularpressure signal, including, but not limited to a pacemaker,defibrillator, electrocardiogram monitor, blood pressure monitor, drugpump, insulin monitor, or neurostimulator. An example of a suitable IMDthat may be used in various exemplary embodiments is the CHRONICLE®monitoring device available from Medtronic, Inc. of Minneapolis, Minn.,which includes a mechanical sensor capable of detecting a ventricularpressure signal. In a further embodiment, IMD 100 is any device that iscapable of sensing ventricular pressure and providing pacing and/ordefibrillation to the heart. Another example of an IMD capable ofsensing pressure-related parameters is described in commonly assignedU.S. Pat. No. 6,438,408B1 issued to Mulligan et al. on Aug. 20, 2002.

Processor 102 may be implemented with any type of microprocessor,digital signal processor, application specific integrated circuit(ASIC), field programmable gate array (FPGA) or other integrated ordiscrete logic circuitry programmed or otherwise configured to providefunctionality as described herein. Processor 102 executes instructionsstored in digital memory 104 to provide functionality as describedbelow. Instructions provided to processor 102 may be executed in anymanner, using any data structures, architecture, programming languageand/or other techniques. Digital memory 104 is any storage mediumcapable of maintaining digital data and instructions provided toprocessor 102 such as a static or dynamic random access memory (RAM), orany other electronic, magnetic, optical or other storage medium.

As further shown in FIG. 1, IMD 100 may receive one or more cardiacleads for connection to circuitry enclosed within the housing. In theexample of FIG. 1, IMD 100 receives a right ventricular endocardial lead118, a left ventricular coronary sinus lead 122, and a right atrialendocardial lead 120, although the particular cardiac leads used willvary from embodiment to embodiment. In addition, the housing of IMD 100may function as an electrode, along with other electrodes that may beprovided at various locations on the housing of IMD 100. In alternateembodiments, other data inputs, leads, electrodes and the like may beprovided. Ventricular leads 118 and 122 may include, for example, pacingelectrodes and defibrillation coil electrodes (not shown) in the eventIMD 100 is configured to provide pacing, cardioversion and/ordefibrillation. In addition, ventricular leads 118 and 122 may deliverpacing stimuli in a coordinated fashion to provide biventricular pacing,cardiac resynchronization, extra systolic stimulation therapy or otherbenefits. IMD 100 obtains pressure data input from a pressure sensorthat is carried by a lead shown in FIG. 1, such as right ventricularendocardial lead 118. A pressure sensor may alternatively be located onan independent lead provided for deployment of the pressure sensor inthe right or left ventricle for obtaining a ventricular pressure signal.IMD 100 may also obtain input data from other internal or externalsources (not shown) such as an oxygen sensor, pH monitor, arterialpressure sensor, accelerometer or the like.

In operation, IMD 100 obtains data about heart 120 via leads 118, 120,122, and/or other sources. This data is provided to processor 102, whichsuitably analyzes the data, stores appropriate data in memory 104,and/or provides a response or report as appropriate. Any identifiedcardiac episodes (e.g. an arrhythmia or heart failure decompensation)can be treated by intervention of a physician or in an automated manner.In various embodiments, IMD 100 activates an alarm upon detection of acardiac event. Alternatively or in addition to alarm activation, IMD 100selects or adjusts a therapy and coordinates the delivery of the therapyby IMD 100 or another appropriate device. Optional therapies that may beapplied in various embodiments may include drug delivery or electricalstimulation therapies such as cardiac pacing, resynchronization therapy,extra systolic stimulation, neurostimulation, or modifications in drugdelivery or electrical stimulation parameters.

FIG. 2 is a block diagram summarizing the data acquisition andprocessing functions for IMD 100. IMD 100 includes a data collectionmodule 206, a data processing module 202, a response module 218 and/or areporting module 220. Each of the various modules may be implementedwith computer-executable instructions stored in memory 104 and executingon processor 102 (shown in FIG. 1), or in any other manner. Theexemplary modules and blocks shown in FIG. 2 are intended to illustrateone logical model for implementing an IMD 100 for monitoring cardiacoutput using ventricular pressure signals, and should not be construedas limiting. Indeed, the various practical embodiments may have widelyvarying software modules, data structures, applications, processes andthe like. As such, the various functions of each module may in practicebe combined, distributed or otherwise differently-organized in anyfashion in or across an IMD system that includes implantable sensors, anIMD and an external programmer.

Data collection module 206 is interfaced with one or more data sources207 to obtain data about the patient. Data sources 207 include anysource of information about the patient's heart or other physiologicalsignals. Data sources 207 include an ECG or EGM source 208 that providescardiac electrical signals such as P-waves or R-waves used to monitorthe patient's heart rhythm. Data sources 207 further include aventricular pressure sensor 210 for obtaining a pressure signal fromwhich cardiac output may be estimated using pulse contour analysismethods as will be described in detail below. Data sources 207 mayinclude other sensors 212 for acquiring physiological signals useful inmonitoring a cardiac condition such as an accelerometer or wall motionsensor, a blood gas sensor such as an oxygen sensor, a pH sensor, orimpedance sensors for impedance changes relating to respiration, lungwetness, or cardiac chamber volumes. The various data sources 207 may beprovided alone or in combination with each other, and may vary fromembodiment to embodiment. Pressure sensor 210 may be embodied as thepressure sensor disclosed in commonly assigned U.S. Pat. No. 5,564,434,issued to Halperin et al., hereby incorporated herein in its entirety.

Data collection module 206 receives data from each of the data sources207 by polling each of the sources 207, by responding to interrupts orother signals generated by the sources 207, by receiving data at regulartime intervals, or according to any other temporal scheme. Data may bereceived at data collection module 206 in digital or analog formataccording to any protocol. If any of the data sources generate analogdata, data collection module 206 translates the analog signals todigital equivalents using an analog-to-digital conversion scheme. Datacollection module 206 may also convert data from protocols used by datasources 207 to data formats acceptable to data processing module 202, asappropriate.

Data processing module 202 is any circuit, programming routine,application or other hardware/software module that is capable ofprocessing data received from data collection module 206. In variousembodiments, data processing module 202 is a software applicationexecuting on processor 102 (FIG. 1) to implement the processes describedbelow for estimating SV from a ventricular pressure signal. Accordingly,data processing module 202 processes ventricular pressure signals forcomputing an estimated SV which may further be used for determining ameasure of cardiac output, as described more fully below.

In an exemplary embodiment, processing module 202 receives data fromventricular pressure sensor 210 and EGM data from EGM sensing electrodes208 from data collection module 206 and interprets the data usingdigital signal processing techniques to compute an estimated strokevolume (in digital units) on a beat-by-beat basis. The stroke volume isthe volume of blood ejected from the ventricle during a cardiac systole.An estimated flow (CO) can be computed from the estimated stroke volumeand a measure of the heart rate. The estimated CO and/or intermediatecomputational results may be stored in memory 204, which may correspondto hardware memory 104 shown in FIG. 1, or may be implemented with anyother available digital storage device. CO monitoring data may beacquired and stored on a scheduled or triggered basis to allow trends inCO to be monitored for use in managing the hemodynamic status of thepatient.

When a change in CO based on the estimated SV is detected, processingmodule 202 may trigger an appropriate response. Responses may beactivated by sending a digital message in the form of a signal, passedparameter or the like to response module 218 and/or reporting module220.

Reporting module 220 is any circuit or routine capable of producingappropriate feedback from the IMD to the patient or to a physician. Invarious embodiments, suitable reports might include storing data inmemory 204, generating an audible or visible alarm 228, producing awireless message transmitted from a telemetry circuit 230. Reports mayinclude information about the estimated stroke volume, cardiac output,pressure measurements derived from the right ventricular pressuresignal, heart rhythm, time and date of data collection, and any otherappropriate data. In a further embodiment, the particular responseprovided by reporting module 220 may vary depending upon the severity ofthe hemodynamic change. Minor episodes may result in no alarm at all,for example, or a relatively non-obtrusive visual or audible alarm. Moresevere episodes might result in a more noticeable alarm and/or anautomatic therapy response.

Telemetry circuitry 230 communicates data from IMD 100 to an externaldevice adapted for bidirectional telemetric communication with IMD 100.The external device receiving the wireless message may be aprogrammer/output device that advises the patient, a physician or otherattendant of serious conditions, e.g., via a display or a visible oraudible alarm. Information stored in memory 204 may be provided to anexternal device to aid in diagnosis or treatment of the patient.Alternatively, the external device may be an interface to acommunications network such that IMD 100 is able to transfer data to anexpert patient management center or automatically notify medicalpersonnel if an extreme episode occurs.

Response module 218 is any circuit, software application or othercomponent that interacts with any type of therapy-providing system 224,which may include any type of therapy delivery mechanisms such as a drugdelivery system 222, neurostimulation 226 and/or cardiac stimulation224. In some embodiments, response module 218 may alternatively oradditionally interact with an electrical stimulation therapy deviceintegrated with IMD 100 to deliver pacing, cardiac resynchronizationtherapy, extra systolic stimulation, cardioversion, defibrillationand/or any other therapy. Accordingly, the various responses that may beprovided by IMD 100 vary from simple storage of data to actual provisionof therapy in various embodiments. Any therapy provided may becontrolled or adjusted in response to a hemodynamic change observed as achange in stroke volume or cardiac output estimated from a rightventricular pressure signal or in response to a combination ofphysiological signals acquired by data sources 207. Drug dosage may beadjusted according to episode severity, for example, or electricalstimulation parameters can be adjusted in response to observeddeterioration in hemodynamic measures.

The various components and processing modules of IMD 100 may be housedin a common housing such as that shown in FIG. 1. Alternatively,portions of IMD 100 may be housed separately. For example, portions ofthe therapy delivery system 224 could be integrated with IMD 100 orprovided in a separate housing, particularly where the therapy deliverysystem includes drug delivery capabilities. In this case, responsemodule 218 may interact with therapy delivery system 224 via anelectrical cable or wireless link.

FIG. 3 is a flow chart summarizing a method 300 for computing anestimated SV from a right ventricular pressure signal for use in COmonitoring. The steps shown in the flow chart of FIG. 3, as well as theother flow charts presented herein, may be implemented within an IMD,such as the IMD shown in FIG. 1, or across an IMD system or patientmanagement system. Generally, the EGM and RVP signals will be acquiredby an IMD and initially processed to obtain beat-by-beat SV estimates indigital units along with associated heart rate data, which may be usedto compute CO in digital units. The digital estimated SV and heart ratedata can be uplinked to an external programmer or monitor for furtherprocessing to determine CO in physical units of L/min.

Cardiac output monitoring may be enabled upon detecting a predeterminedtriggering event, on a scheduled basis, or manually by a clinician,patient or other caregiver using an external device. When cardiac outputmonitoring is enabled, the EGM signal is sensed at step 255 to allowdetection of the onset of a cardiac cycle based on a detected R-waveevent at step 260. A detected R-wave event may be an R-wave detected onan EGM signal but could alternatively be a pacing event or otherelectrical signal appropriate for marking the start of a cardiac cycle.The present invention is not limited, however, to the use of an EGMsignal or pacing signal for detecting the start of a cardiac cycle.Other physiological signals could be substituted from which anapproximation of the start of the cardiac cycle may be made. In onealternative embodiment, a pressure signal may be used to detect thestart of the cardiac cycle. For example, a predetermined thresholdcrossing of pressure amplitude or dP/dt determined from the RVP signal(or another pressure signal) may be detected as an R-wave related eventand used as the starting point of a cardiac cycle for the purposes ofthe present invention.

Once an R-wave event is detected at step 260, the RVP signal is acquiredfor a predetermined interval of time, or analysis window, during whichanalysis of the RVP signal will be performed for estimating strokevolume. The RVP signal data is stored in a memory buffer to allow thesignal to be analyzed. In one embodiment, RVP signal data is stored in amemory buffer for about 500 msec following an R-wave event detection.Anomalous cardiac cycles associated with arrhythmias, prematurecontractions, or noise may be rejected.

At step 270, a number of landmark features or points are identified onthe RVP signal during the analysis window. As will be described indetail below, the amplitude of the RVP at the landmark points and/or thetime of the landmark points relative to the R-wave event detection willbe used for computing an estimated stroke volume at step 275. The CO canthen be computed at step 280 from the estimated SV and the heart ratedetermined from intervals between successive R-wave events. The CO maybe computed on a beat-by-beat basis or may be calculated over aninterval of time for which the heart rate and an averaged estimated SVis determined.

Data processing circuitry 202 (in FIG. 2) within the IMD may be used tocompute the estimated CO in digital units at step 280. The estimated COmay be computed on a beat-by-beat or interval basis allowing trends inCO to be determined by data processing circuitry 202. Changes inestimated CO detected by data processing circuitry 202 can be respondedto appropriately by response module 218 (FIG. 2). Thus, estimated CO maybe used in a closed-loop control algorithm for controlling therapydelivery. Estimated CO data may additionally or alternatively be storedin IMD memory for uplinking to an external device for review andanalysis by a clinician.

After uplinking to an external device, the estimated SV in digital unitsmay be converted to physical units of volume such that CO may bedetermined in units of volume per unit time. The estimated SV isconverted to units of volume by multiplying by a calibration gain and/oradding a calibration offset value. The calibration values are determinedfor a given pressure sensor and may be individualized for a givenpatient. In some embodiments, non-linear calibration factors may be usedfor converting estimated SV values to actual values in volume units. Ifmethod 300 is fully implemented in an IMD, calibration factors may bedownlinked to the IMD for performing conversion of SV and/or CO datafrom digital to physical units.

FIG. 4 shows a RVP signal and illustrates one method for estimating SVfrom the RVP signal. A recording of a RVP signal 10 is shown over aperiod of approximately two cardiac cycles. The RVP signal 10 is shownsuperimposed on a pulmonary artery pressure signal 12 for the purpose ofillustrating the usefulness of landmark pressure points determined froma RVP signal in estimating SV. Ejection of blood from the rightventricle increases flow and pressure in the pulmonary artery.Estimation of flow from arterial signals using pulse contour analysis isuseful in monitoring a patient's cardiac output. The use of arterialpressure waveforms for monitoring CO using pulse contour cardiac outputtechniques are known in the art. In the present invention, the RVPsignal is analyzed to determine landmark pressure points that correlateto events in the pulmonary artery pressure signal and are thereforeuseful in estimating stroke volume in a modified pressure pulse contouranalysis approach.

The pulmonic valve opens when pressure within the right ventricleexceeds the pulmonary artery diastolic pressure. Blood is then ejectedfrom the right ventricle and forward flow occurs. The pulmonary arterydiastolic (PAD) pressure can be estimated as being equal to the pressurein the right ventricle at the time that the maximum rate of pressurerise, dP/dtmax, occurs in the right ventricle. Methods for deriving ePADfrom a ventricular pressure signal are generally disclosed in U.S. Pat.No. 5,368,040 issued to Carney, U.S. Pat. No. 5,626,623 issued to Kievalet al., and U.S. Pat. No. 6,580,946 B2 issued to Struble, all of whichpatents are hereby incorporated herein in their entirety.

In accordance with the method described above in conjunction with FIG.3, a RVP signal analysis window 16 is applied upon detection of anR-wave event 14. The RVP signal 10 is stored during window 16 to allowan analysis of the systolic portion of the RVP signal. During thisanalysis window, the RVP amplitude at the time of dP/dtmax is determinedas the estimated PAD (ePAD) 18. The peak RV systolic pressure,RVP(peak), 20 is also determined during the analysis window 16. Thedifference between the RVP(peak) 20 and ePAD 18 can be determined as anestimated stroke volume (eSV) 22. This method for estimating SV assumesthat the RV pressure generated following opening of the pulmonic valveis correlated to forward flow. The estimated SV based on the pressuredifference during the ejection phase does not take into accountvariations in vascular impedance or the ejection interval but mayprovide a useful measure for monitoring CO.

An estimated CO can be computed from the estimated SV by dividing theeSV by the RRI 24 measured for the current cardiac cycle. If desired,the estimated CO can be converted later to units of volume per unit timeusing calibration factors as described above.

FIGS. 5 through 9 illustrate another method for computing an estimatedSV using pulse contour analysis of the RVP signal. FIG. 5 illustrates amethod for determining an integration interval for use in computing apressure pulse contour integral. Following detection of an R-wave event14, the RVP signal 10 is acquired and stored over a predeterminedanalysis window 16 to allow landmark points to be determined from thesystolic portion of the RVP signal. The time at which the maximum rateof RVP rise (dP/dtmax) occurs, which corresponds to the ePAD 18, isdetermined as an integration start time (IST) 28. This integration starttime 28 approximates the end of the pre-ejection interval (PEI) and thetime of pulmonic valve opening, which marks the start of forward flowfrom the right ventricle.

An integration end time (IET) 30 is defined as the time at which thedecreasing RVP signal amplitude equals the ePAD 18. The time at whichthe RVP equals the ePAD 18 is one approach to approximating the time ofpulmonic valve closure, which marks the end of forward flow from theright ventricle. The area A1 under the RVP signal 10 between theintegration start time 28 and integration end time 30 is computed. Thisarea A1 will be used in computing an estimated stroke volume as will befurther described below.

In one embodiment, the area A1, bounded by the RVP signal 10, the zerobaseline, and the integration start time 28 and integration end time 30,may be used as an estimated stroke volume. However, this area A1 mayoverestimate the stroke volume due to inclusion of areas bounded by theRVP signal that do not correlate to actual forward flow from the rightventricle. FIGS. 6 through 9 illustrate the computation of correctionareas that may be used for correcting the area A1 for determining a moreaccurate estimate of stroke volume.

In FIG. 6, area A2 is defined as the area bounded by ePAD 18 and thezero baseline between the integration start time 28 and integration endtime 30. Area A2 can be thought of as area related to pressure generatedduring the pre-ejection interval that does not contribute to forwardflow. Area A2 may be subtracted from area A1 to provide a more accurateestimated stroke volume.

The accuracy of the estimated SV computed from the RVP contour willdepend in part on the accuracy of the estimated time of valve openingand closure. If the integration end time 30 occurs after pulmonic valveclosure, the area under the RVP signal calculated as an estimate of SVmay overestimate the SV. The pulmonary artery pressure at the time ofvalve closure may be closer to the mean pulmonary artery pressure duringa cardiac cycle rather than the ePAD. Hence, the time of pulmonic valveclosure may be more accurately estimated as the time at which the RVPsignal amplitude equals the mean pulmonary artery pressure (MPAP). MPAPmay be estimated from the RVP signal according to methods generallydisclosed in U.S. patent application Ser. No. 09/997,753, filed Nov. 30,2001, hereby incorporated herein in its entirety.

FIG. 7 illustrates a method for computing an estimated mean pulmonaryartery pressure from the RVP signal. The pulmonic valve closes at thetime of the dicrotic notch 34 in the PAP waveform 12. The correspondingMPAP is computed as a weighted average of the peak RVP 20 and ePAD 18.Weighting factors are determined from the systolic and diastolic timeintervals measured during the cardiac cycle. A ratio of the systolictime interval (STI) to the total RRI is used as the peak RVP weightingfactor. The STI can be measured as the time interval beginning at R-waveevent detection 14 and ending at the previously determined integrationend time 30. The STI can be defined generally as an interval extendingfrom a detection of the start of systole, such as R-wave event detection13 to a detection of the end of systole, such as dP/dt_(min). The ratioof the diastolic interval to the total RRI is used as the ePAD weightingfactor. The diastolic interval can be determined as the differencebetween the RRI and the measured systolic time interval. Thus, the MPAPcan be estimated from the RVP signal 10 according to the followingequation {1}:MPAP={RVP(peak)*(STI/RRI)}+{ePAD*(RRI−STI)/RRI}.  {1}

Referring again to FIG. 6, the MPAP 32 computed according to the aboveequation can be used to identify a corrected integration end time (CIET)36. The time at which pulmonic valve closure occurs, i.e. the time atwhich forward flow ends, may be more accurately estimated on the RVPcurve 10 as the time at which the descending RVP signal amplitude equalsthe estimated MPAP 32. The area A3 under the RVP signal 10 and to theright of the corrected integration end time 36 may cause the SV computedfrom area A1 to be overestimated. This area A3 may be approximated as atriangular area computed from the following equation {2}:A3=0.5*(MPAP−ePAD)*(IET−CIET)  {2}

In some embodiments, the correction area A3 is subtracted from theentire area A1 under the RVP signal 10 for estimating the SV moreaccurately.

FIG. 8 illustrates the computation of a third area A4 that may be usedto correct an estimated SV computed using the total integrated area A1under the RVP waveform 10. The correction area A4 is approximated as atriangle and computed from the following equation {3}:A4=0.5*{(MPAP−ePAD)*(CIET−IST)}  {3}

In some embodiments, the correction area A4 is subtracted from theentire area A1 under the RVP signal 10 for estimating the SV moreaccurately.

FIG. 9 illustrates the computation of a fourth correction area A5 thatmay be used to correct the total area A1, as an estimate of SV computedfrom the RVP waveform. Computation of an estimated SV from a RVPwaveform can be limited in accuracy due to changes in pulmonary vascularresistance, or the load against which the ventricle must eject blood.Changes in pulmonary vascular resistance are not accounted for bypressure signal analysis alone. At least a portion of the pressuredeveloped by the right ventricle contributes to overcoming pulmonaryvascular resistance before producing forward flow. The effect of changesin pulmonary vascular resistance on SV may be corrected for by computinga fourth correction area A5. The area A5 is computed based on a “run-offslope.”

The run-off slope (ROS) 40 is the slope between the MPAP 32 at thecorrected integration end time 36 and ePAD 18 at the integration starttime 29 of the next cardiac cycle. The run-off slope 40 represents thefall in pressure that occurs in the pulmonary vascular system afterpulmonic valve closure occurs, prior to the start of the next ejectionphase. In patients with high pulmonary vascular resistance, thepulmonary artery diastolic pressure will be high. A greater contributionof the generated RVP will be required to overcome the pulmonary vascularresistance before producing forward flow. When ePAD increases as aresult of increased pulmonary vascular resistance, the run-off slopewill decrease.

The run-off slope 40 is computed using equation {4}:ROS=(MPAP−ePAD)/(RRI−CIET+IST  {4}

The time interval 46 over which the run-off slope 40 is computed can bedetermined using time measurements (RRI, IST 28 and CIET 36) from thecurrent cardiac cycle. Thus data regarding the subsequent cardiac cycleis not required for computing ROS 40. The time interval 46 can becomputed as the RRI less the corrected integration end time 36 plus theintegration start time 28 of the current cardiac cycle, rather than ofthe next cardiac cycle. The resulting time interval is approximately theinterval of time 46 between pulmonic valve closure and pulmonic valveopening. Likewise, in computing the ROS, ePAD from the current cardiaccycle can be substituted for ePAD from the subsequent beat. Bysubstituting IST and ePAD from the current beat, all computations arisefrom the current cardiac cycle, simplifying the implementation.

The run-off slope 40 is applied over the integration time interval tocompute an area A5 used to account for changes in pulmonary vascularresistance when estimating SV. The area A5 is computed as the area of atriangle 42 defined by the run-off slope 40 applied between theintegration start time 42 and the corrected integration end time 36. Thearea A5 is computed from the following equation {5}:A5=0.5*{(CIET−IST)*(ROS*(CIET−IST))}  {5}

Another way of illustrating the effect of variations in pulmonaryvascular resistance on SV estimated from the RVP waveform 10 is shown bythe shaded region 44. Shaded region 44 is an area equal to triangulararea 42 but is applied to the pulse contour of the RVP waveform 10during the ejection phase, which is defined by the integration starttime 28 and the corrected integration end time 36. The correction areaA5 will increase as ROS 40 increases. A decrease in pulmonary vascularresistance will increase the computed ROS 40 due to a greater differencebetween MPAP and ePAD. With a decrease in pulmonary vascular resistance,greater forward flow may be produced by the developed RVP. Thus, thecorrection area A5 will be greater as ROS 40 increases representing anincrease in forward flow as pulmonary vascular resistance decreases.

When pulmonary vascular resistance increases, the ROS slope 40 willdecrease, decreasing the correction area A5. The decreased correctionarea A5 is analogous to a decrease in forward flow in response todeveloped RVP due to increased pulmonary vascular resistance. An overallestimated stroke volume will thus be corrected for changes in pulmonaryvascular resistance by inclusion of A5 in the computation of theestimated stroke volume. In some embodiments, the area A5 or its contourmay be used in computing an estimated SV without additional computationsof A1 through A4.

FIG. 10 illustrates the computation of a pulse contour integral (PCI) 38from the total area A1 under RVP waveform 10 between integration starttime 20 and integration end time 30 and the correction areas A2, A3, A4and A5. PCI 38 is computed according to the following equation {6}:PCI=A1−A2−bA3−cA4+dA5  {6}

wherein the coefficients b, c and d may be 0 or 1 or determined to beanother real or non-linear weighting factor based on experimental orclinical studies or individual patient results. The decision to activateor not activate correction areas A3, A4 and A5, e.g., using a value of 1or 0 for the respective coefficients b, c, and d, may be made based onthe type of medical condition. For example, conditions such as pulmonaryhypertension, congestive heart failure, fast relaxation (lusitropicfunction), large heart rate range during data acquisition, or othermedical conditions may be factors in determining the criteria foractivating the correction areas A3, A4, and A5 in computing PCI 38 anddetermining the appropriate values for coefficients b, c, and d. Theresulting area of PCI 38 is a useful estimate of stroke volume. Whencomputed by an IMD processor, the stroke volume estimated as the PCI 38is determined in digital units according to equation {6} above. Thisestimated stroke volume may be stored by the IMD and/or used in aclosed-loop fashion for controlling IMD therapies. In lieu of or inaddition to the foregoing, calibration data can be wirelessly downloadedto the IMD so that a memory structure of the IMD retains any presetthresholds (e.g., set by a clinician) to enhance therapy delivery.

FIG. 11 is a plot of estimated stroke volume computed using the RVPpulse contour method provided by the invention versus stroke volumemeasured by placing a flow probe on the pulmonary artery in a caninestudy (n=1). A strong correlation (R²=0.83) is demonstrated between theestimated stroke volume (y-axis), computed as the PCI of the RVPwaveform as described above, and the actual measured stroke volume(x-axis). Based on the linear relation between the computed PCI and themeasured stroke volume, linear calibration factors, a gain and anoffset, may be determined to convert the PCI in digital units to unitsof volume:eSV(L)=gain*PCI+offset.  {7}

In the example shown in FIG. 11, the linear regression of PCI andmeasured stroke volume provides the following equation for computing anestimated stroke volume to units of volume from the PCI in digitalunits:eSV(L)=0.019*PCI+0.017  {8}

FIG. 12 is a flow chart summarizing the steps performed in a method formonitoring cardiac output using the RVP pulse contour method forestimating stroke volume described in conjunction with FIGS. 5 through9. At step 305, an R-wave or related event is detected to indicate thestart of a cardiac cycle. Detection of an R-wave event sets the start ofan analysis window during which the RV pressure signal is acquired andstored in a memory buffer at step 310. The analysis window is set to aduration that will include the systolic time interval or at least theejection time interval.

At step 315, an integration start time is set based on an estimated timeof pulmonic valve opening. In the method described above in conjunctionwith FIG. 5, the integration start time is set at the time that the RVPsignal amplitude equals the estimated pulmonary artery diastolicpressure (ePAD), which corresponds to the maximum rate of RVP rise(dP/dt max). Other methods for estimating the time of pulmonic valveopening, including other methods that rely on alternative physiologicalsignals, could be utilized in setting the integration start time (IST)at step 315. If the IST is illogical in its timing relative to an R-waveevent detection the current cardiac cycle would be ignored.

At step 320, the integration end time (IET) is set based on an estimatedtime of pulmonic valve closure. In the method described above inconjunction with FIG. 5, the integration end time is set at the timethat the falling RVP signal amplitude equals ePAD. Other methods forestimating pulmonic valve closure time could be utilized, includingmethods that rely on alternative physiological signals. For example,methods could be conceived that utilize acoustical signals for detectingthe time of pulmonic valve opening and closure for setting anintegration start and end time to be applied to the RVP signal at steps315 and 320. If the IET is illogical in its timing relative to the IST,then the entire cardiac cycle would be ignored.

At step 325, the area A1 under the RVP waveform is determined byintegrating the RVP signal over the time interval defined by theintegration start time and integration end time. In some embodiments,the area A1 may be used as a measure of estimated stroke volume.However, a more sensitive and accurate estimate of stroke volume may beobtained by correcting the area A1 using a number of correction areasthat are also computed by identifying selected features of the RVPwaveform. Various logical criteria could be set up to ensure a validrange of values for A1. If the criteria were not met, the entire cardiaccycle would be ignored.

At step 330, correction area A2 is computed as the area under theestimated pulmonary artery diastolic pressure (ePAD) between theintegration start time and integration end time. Various logicalcriteria could be set up to ensure a valid range of values for A2. Ifthe criteria were not met, the entire cardiac cycle would be ignored.

At step 335, a mean pulmonary artery pressure (MPAP) estimate isdetermined from the RVP signal as described above in conjunction withFIG. 7. The MPAP is used to set a corrected integration end time thatoccurs earlier than the integration end time set based on ePAD at step320. A correction area A3 is computed at step 340 as the area under theRVP waveform between the corrected integration end time and thepreviously set integration end time. Area A3 may be approximated as atriangle. If the MPAP estimate corresponds to a corrected integrationend time that occurs later in time than the integration end time setbased on ePAD, the corrected integration end time is considered to be ananomalous result. The entire cardiac cycle is ignored if the correctedintegration end time is later than IET due to the illogical condition ofthe estimated MPAP being less than ePAD.

At step 345, correction area A4 is computed based on the MPAP estimateand the corrected integration end time. Correction area A4 may beapproximated as a triangle defined by ePAD, MPAP, and the integrationstart and end time as described previously in conjunction with FIG. 8.

At step 350 a run-off slope is computed as the slope between the MPAPand ePAD over the diastolic and pre-ejection intervals. The run-offslope is applied over the integration interval starting at theintegration start time and ending at the corrected integration end timeto compute a correction area A5 as described in conjunction with FIG. 9.Correction area A5 may be used to account for variations in pulmonaryvascular resistance.

The pulse contour integral (PCI) is determined at step 360 from thecomputed areas A1, A2, A3, A4, and A5, wherein each area may be assigneda coefficient or weighting factor. The PCI is an estimate of strokevolume for the given cardiac cycle. The PCI and the RRI measured for thecurrent cardiac cycle is used to compute cardiac output at step 365 on abeat-by-beat basis. Cardiac output may also be determined on an averagedbasis over multiple cardiac cycles, and beat-by-beat or averaged cardiacoutput measurements may be used to monitor trends in hemodynamic statusof a patient. If the PCI value does not meet a set of predefined logicalPCI range criteria, the current cardiac cycle is ignored.

FIG. 13 is a flow chart summarizing a method for monitoring thehemodynamic status of a patient. Method 400 is executed by an IMD on abeat-by-beat basis to obtain pulmonary artery pressure data and cardiacoutput measures. Such data can be used to assess trends in hemodynamicstatus of patient with congestive heart failure, providing usefulinformation for managing heart failure therapies.

At step 405, ePAD is determined from the RVP signal as the RVP amplitudeat the time of the maximum dP/dt. At step 410, MPAP is estimated fromthe RVP signal according to the weighted average of the peak RVP andePAD as described previously and as generally disclosed in theabove-referenced U.S. patent application Ser. No. 09/997,753.

At step 415, the patient's stroke volume is estimated from the RVPsignal based on a determination of landmark features of the RVP signalin accordance with the methods described above. At step 410 the heartrate (HR) is determined for use in computing a measure of CO from theestimated SV at step 415. For a beat-by-beat computation of CO, theestimated SV is divided by the RRI. In binary arithmetic, the SV/RRIquotient in digital units is multiplied by a conversion constant of60000.

At step 430 a measure of pulmonary vascular resistance (PVR) is computedfrom the estimated CO (flow) and the estimated pulmonary arterypressures:PVR=(MPAP−ePAD)/CO  {9}

At step 435, the ePAD, MPAP, estimated SV, computed CO and PVR valuesare stored. Data may be stored in a variety of formats includingbeat-by-beat data storage, histogram storage, or storage of statisticalaspects of the beat-by-beat values. In the example shown in FIG. 13, amean value and range (high and low) for each parameter measured during amonitoring episode of a series of cardiac beats is stored.

The pulmonary pressure and flow data derived from the RVP signal is madeavailable to a clinician for further review or analysis by uplinking thestored data to an external device. The derived pressure and flow data isvaluable in managing the treatment of congestive heart failure where thegoal is to reduce filling pressures while maintaining adequate CO. Thederived pressure and flow data can be uplinked in real-time to provideinformation to the clinician regarding the hemodynamic response toclinical interventions. The data can also be made available for use bythe IMD in real-time, closed-loop therapy control algorithms responsiveto relative changes in estimated SV or estimated CO.

The detailed embodiments described herein have referred primarily to theuse of a RVP signal for estimating pulmonary artery pressures andright-side stroke volume there from. However, the methods describedherein can be adapted for application to LVP signals wherein LVP signalfeatures are selected for estimating aortic pressures and computingtriangular or polygonal areas or computing a pulse contour integral forestimating left-sided flow. For example, an estimated aortic diastolicpressure may be derived as the LVP at dP/dt max and used as anintegration start time. The time at which the descending portion of theLVP curve reaches the estimated aortic diastolic pressure may be used asan integration end time. A mean aortic pressure may be estimated fromthe LVP signal using a method analogous to the MPAP estimation methodusing the RVP signal for determining a corrected integration end time.Likewise, a number of correction areas could be defined and computedusing various landmark pressure and time points selected from the LVPsignal.

The invention provides a method and apparatus for hemodynamic monitoringbased on ventricular pressure signals. Variations to the methodsdescribed herein may be conceived by one having skill in the art and thebenefit of the teachings provided herein without departing from thescope of the invention. The embodiments described herein are intended toillustrate exemplary methods for practicing the invention and should notbe interpreted as limiting with regard to the following claims.

1. A system, comprising: means for sensing a cardiac electrogram (EGM)signal of the heart; means for sensing a right ventricular pressure(RVP) signal; means for computing an estimated stroke volume using thesensed EGM signal and the sensed RVP signal; wherein the means forcomputing an estimated stroke volume comprises means for computing a RVPpulse contour integral by: identifying an integration start timecorresponding to an estimated time of pulmonic valve opening;identifying an integration end time corresponding to an estimated timeof pulmonic valve closure; and computing a plurality of correction areasused to adjust the area under the right ventricular pressure signalbetween the integration start time and the integration end time; andmeans for one of displaying and storing in a memory structure at leastone of: the RVP pulse contour, the estimated stroke volume, the rightventricular pressure signal, the area.
 2. A system according to claim 1wherein the means for sensing the right ventricular pressure signalcomprises: means for detecting an R-wave event from the sensed EGMsignal; means for setting an analysis window for a predeterminedinterval of time following the R-wave event detection; and means foracquiring and storing the RVP signal during the analysis window.
 3. Asystem according to claim 1 wherein the means for computing an estimatedstroke volume comprises means for: deriving an estimated pulmonaryartery diastolic pressure from the RVP signal; deriving a peak rightventricular pressure amplitude from the RVP signal; and computing adifference between the estimated pulmonary artery diastolic pressure andthe peak right ventricular pressure amplitude.
 4. A system according toclaim 1 wherein the means for computing an estimated stroke volumecomprises means for determining the estimated time of pulmonic valveopening as a time corresponding to a maximum rate of pressure rise inthe right ventricular pressure signal.
 5. A system according to claim 1wherein the means for computing an estimated stroke volume comprisesmeans for determining estimated time of pulmonic valve closure as a timecorresponding to a right ventricular pressure amplitude occurring on adescending portion of the right ventricular pressure signal and equalinga right ventricular pressure amplitude at the integration start time. 6.A system according to claim 1 wherein the means for computing anestimated stroke volume comprises means for: deriving an estimatedpulmonary artery diastolic pressure using the right ventricular pressuresignal and the EGM signal, and computing the area below the estimatedpulmonary artery diastolic pressure and between the integration starttime and the integration end time.
 7. A system according to claim 1wherein the means for computing an estimated stroke volume comprisesmeans for: deriving a mean pulmonary artery pressure using the RVPsignal and the EGM signal; identifying a corrected integration end timecorresponding to a time that a RVP signal amplitude occurring on adescending portion of the right ventricular pressure signal equals theestimated mean pulmonary artery pressure; and computing an area underthe right ventricular pressure signal between the corrected integrationend time and the integration end time.
 8. A system according to claim 1wherein the means for computing an estimated stroke volume comprisesmeans for: deriving a mean pulmonary artery pressure using the RVPsignal and the EGM signal; identifying a corrected integration end timecorresponding to a time that a RVP signal amplitude occurring on adescending portion of the right ventricular pressure signal equals theestimated mean pulmonary artery pressure; deriving an estimatedpulmonary artery diastolic pressure using the right ventricular pressuresignal and the EGM signal; computing a triangular area having sidesdefined by a horizontal line corresponding to the estimated pulmonaryartery diastolic pressure, a vertical line corresponding to thecorrected integration end time, and a line segment intersecting thehorizontal line at a point on a descending portion of the RVP signalequal in amplitude to the derived mean pulmonary artery pressure andintersecting the vertical line at a point on an ascending portion of theRVP signal equal to the estimated pulmonary artery diastolic pressure.9. A system according to claim 1 wherein the means for computing anestimated stroke volume comprises means for: computing a correction areacorresponding to changes in pulmonary vascular resistance.
 10. A systemaccording to claim 9 wherein the means for computing a correction areacorresponding to changes in pulmonary vascular resistance comprisesmeans for: deriving a mean pulmonary artery pressure using the RVPsignal and the EGM signal; identifying a corrected integration end timecorresponding to a time that a RVP signal amplitude occurring on adescending portion of the right ventricular pressure signal equals theestimated mean pulmonary artery pressure; deriving an estimatedpulmonary artery diastolic pressure using the right ventricular pressuresignal and the EGM signal; computing a slope between the mean pulmonaryartery pressure and the estimated pulmonary artery diastolic pressureover a time interval derived from the EGM signal corresponding to adiastolic interval and pre-ejection interval; computing the area of atriangle defined by the slope applied between the integration start timeand the corrected integration end time.
 11. A system according to claim1 wherein the means for computing the estimated stroke volume comprisesmeans for computing the RVP pulse contour integral as a function of thearea under the RVP curve between the integration start time and theintegration end time and the plurality of correction areas.
 12. A systemaccording to claim 1 further comprising means for computing a cardiacoutput from the estimated stroke volume and a heart rate derived fromthe EGM signal.
 13. A system according to claim 1 further comprisingmeans for computing a cardiac output using the estimated stroke volumeand a heart rate derived from the EGM signal.
 14. A system formonitoring the hemodynamic status of a patient, comprising: means forsensing a cardiac electrogram (EGM) signal of the heart; means forsensing a right ventricular pressure (RVP) signal; means for computingan estimated stroke volume using the sensed EGM signal and the sensedRVP signal; means for deriving a mean pulmonary artery pressure usingthe RVP signal and the EGM signal; and means for deriving an estimatedpulmonary artery diastolic pressure using the right ventricular pressuresignal and the EGM signal; and means for computing a pulmonary vascularresistance using the sensed EGM signal and the sensed RVP signal by:computing a pressure difference between the mean pulmonary arterypressure and the estimated pulmonary artery diastolic pressure; andcomputing a cardiac output metric using the estimated stroke volume anda heart rate derived from the EGM signal; dividing the pressuredifference by the cardiac output; and means for one of displaying andstoring in a memory structure at least one of: the cardiac outputmetric, the estimated stroke volume, the heart rate, the pressuredifference, the pulmonary vascular resistance, the right ventricularpressure, the mean pulmonary artery pressure, the estimated pulmonaryartery diastolic pressure.